Computer Vision Machine Learning Engineer, Python

Anduril Industries is a defense technology company with a mission to transform U.S. and allied military capabilities with advanced technology. By integrating the expertise, technology, and business model of 21st-century innovators into the defense industry, Anduril is reshaping how military systems are designed, built, and sold. Our family of systems is powered by Lattice OS, an AI-driven operating system that converts vast data streams into a real-time, 3D command and control center. As the world enters a period of strategic competition, Anduril is dedicated to providing autonomy, AI, computer vision, sensor fusion, and networking technology to the military rapidly. The Vehicle Autonomy (Robotics) team at Anduril develops aerial and ground-based robotic systems, taking products like Ghost, Anvil, and the Sentry Tower from conceptual designs to operational systems. We collaborate closely with specialist teams such as Perception, Autonomy, and Manufacturing to tackle some of the most significant challenges facing our customers. We are seeking a Computer Vision / Machine Learning Engineer to utilize the latest research in order to solve our toughest challenges and must be eligible to obtain and hold a U.S. DoD Security Clearance. This position will be located at our headquarters in Costa Mesa, CA (relocation benefits provided).

What You'll Do:

• Propose and prototype innovative solutions to address real-world challenges using state-of-the-art techniques.
• Curate datasets for evaluating performance and tracking trends over time.
• Develop and maintain core ML pipelines.
• Train and deploy deep learning models for real-time applications.

Core Requirements:

• MS or PhD in Machine Learning, Robotics, or Computer Science with a focus on Computer Vision; or a BS in Computer Science, Machine Learning, Electrical Engineering, or related fields.
• 3+ years of experience developing and benchmarking ML algorithms on large-scale datasets.
• High proficiency in Python and experience with deep learning frameworks such as PyTorch and TensorFlow.
• Experience working with OpenCV, deploying models with TensorRT and ONNX, and writing/maintaining automated continuous integration tests.
• Experience in one or more areas: Object Detection, Object Tracking, Instance Segmentation, Semantic Segmentation, Semantic Change Detection, Visual Odometry, SLAM, Multi-view Geometry, Structure from Motion, 3D Geometry, Discriminative Correlation Filters, Stereo, Neural 3D Reconstruction, and RGB-D or LIDAR Sensor Fusion.

Preferred Qualifications:

• Experience writing custom TensorRT plugins and troubleshooting remotely deployed software systems.
• Proficiency in C++ in a Linux development environment and CUDA.

Benefits:

• Platinum Healthcare Benefits: Comprehensive medical, dental, and vision plans fully covered for you and a majority for dependents.
• 16 weeks paid parental leave for all caregivers.
• Unlimited provisions with healthy meals and snacks provided at the office.
• Relocation assistance and commuter benefits based on your region.
• Unlimited and incentivized time off.
• A professional development stipend available for all employees.
• 401(k) retirement savings plan (traditional and Roth for U.S. roles).
• Generous company holiday calendar and highly competitive PTO plans.
• Access to mental health resources including therapy and life coaching, along with additional work-life services.

The salary range for this role is estimated between $200,000—$240,000 USD based on various compensation factors. Actual offers may vary based on experience, education, critical skills, and business considerations. Highly competitive equity grants are included in most full-time offers. Anduril is an equal-opportunity employer committed to creating a diverse and inclusive workplace. We value unique individuals who contribute to new paths in defense technology and encourage qualified applicants from all backgrounds to apply. If you are passionate about making a real-world impact, we would love to hear from you!

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